Abstract
We discuss the recent developments in probabilistic relaxation techniques which are used as a tool for contextual sensory data interpretation. The successes of a range of applications of probabilistic relaxation reported in the literature are briefly reviewed. We show that the implementation of a probabilistic relaxation process by means of multilayer perceptron computation has implications on the neural net design methodology. Further, the relationship of probabilistic relaxation to the Hough transform is exposed.
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Kittler, J. (1997). Probabilistic relaxation: Potential, relationships and open problems. In: Pelillo, M., Hancock, E.R. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 1997. Lecture Notes in Computer Science, vol 1223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62909-2_93
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DOI: https://doi.org/10.1007/3-540-62909-2_93
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